Time-gated single-pixel imaging of Cherenkov emission from a medical linear accelerator.

Cherenkov imaging is an ideal tool for real-time in vivo verification of a radiation therapy dose. Given that radiation is pulsed from a medical linear accelerator (LINAC) together with weak Cherenkov emissions, time-gated high-sensitivity imaging is required for robust measurements. Instead of using an expensive camera system with limited efficiency of detection in each pixel, a single-pixel imaging (SPI) approach that maintains promising sensitivity over the entire spectral band could be used to provide a low-cost and viable alternative. A prototype SPI system was developed and demonstrated here in Cherenkov imaging of LINAC dose delivery to a water tank. Validation experiments were performed using four regular fields and an intensity-modulated radiotherapy (IMRT) delivery plan. The Cherenkov image-based projection percent depth dose curves (pPDDs) were compared to pPDDs simulated by the treatment planning system (TPS), with an overall average error of 0.48, 0.42, 0.65, and 1.08% for the 3, 5, 7, and 9 cm square beams, respectively. The composite image of the IMRT plan achieved a 85.9% pass rate using 3%/3 mm gamma index criteria, in comparing Cherenkov intensity and TPS dose. This study validates the feasibility of applying SPI to the Cherenkov imaging of radiotherapy dose for the first time to our knowledge.

Incongruence between confirmed and suspected clinical cases of Japanese encephalitis virus infection.

Background: Japanese encephalitis (JE) is a notifiable infectious disease in China. Information on every case of JE is reported to the superior health administration department. However, reported cases include both laboratory-confirmed and clinically diagnosed cases. This study aimed to differentiate between clinical and laboratory-confirmed cases of Japanese encephalitis virus (JEV) infection, and improve the accuracy of reported JE cases by analyzing the acute-phase serum and cerebrospinal fluid of all reported JE cases in the Sichuan province from 2012 to 2022. Methods: All acute-phase serum and/or cerebrospinal fluid samples of the reported JE cases were screened for IgM(ImmunoglobulinM)to JEV using the enzyme-linked immunosorbent assay (ELISA), and the detection of the viral genes of JEV and 9 other pathogens including enterovirus (EV), using reverse transcription PCR was attempted. Epidemiological analyses of JE and non-JE cases based on sex, age, onset time, and geographical distribution were also performed. Results: From 2012 to 2022, 1558 JE cases were reported in the Sichuan province. The results of serological (JEV-specific IgM) and genetic testing for JEV showed that 81% (1262/1558) of the reported cases were confirmed as JEV infection cases (laboratory-confirmed cases). Among the 296 cases of non-JEV infection, 6 viruses were detected in the cerebrospinal fluid in 62 cases, including EV and the Epstein-Barr virus (EBV), constituting 21% (62/296) of all non-JE cases. Among the 62 non-JEV infection cases with confirmed pathogens, infections with EV and EBV included 17 cases each, herpes simplex virus (HSV-1/2) included 14 cases, varicella- zoster virus included 6 cases, mumps virus included 2 cases, and human herpes viruses-6 included 1 case. Additionally, there were five cases involving mixed infections (two cases of EV/EBV, one case of HSV-1/HSV-2, one case of EBV/HSV-1, and one case of EV/herpes viruses-6). The remaining 234 cases were classified as unknown viral encephalitis cases. Our analysis indicated that those aged 0-15 y were the majority of the patients among the 1558 reported JE cases. However, the incidence of laboratory-confirmed JE cases in the >40 y age group has increased in recent years. The temporal distribution of laboratory-confirmed cases of JE revealed that the majority of cases occurred from May to September each year, with the highest incidence in August. Conclusion: The results of this study indicate that there is a certain discrepancy between clinically diagnosed and laboratory-confirmed cases of JE. Each reported case should be based on laboratory detection results, which is of great importance in improving the accuracy of case diagnosis and reducing misreporting. Our results are not only important for addressing JE endemic to the Sichuan province, but also provide a valuable reference for the laboratory detection of various notifiable infectious diseases in China and other regions outside China.

Partitioned estimation methodology of biological neuronal networks with topology-based module detection.

Parameter estimation of neuronal networks is closely related with information processing mechanisms in neural systems. Estimation of synaptic parameters for neuronal networks was an time consuming task. Due to complex interactions between neurons, computational efficiency and accuracy of estimation methods is relatively low. Meanwhile, inherent topological properties such as core-periphery and modular structures are not fully considered in estimation. In order to improve the efficiency and accuracy of estimation, this study proposes a two-stage PartitionMLE method which introduces detected neuronal modules as topological constraints in estimation. The proposed PartitionMLE method firstly decomposes the system into multiple non-overlapping neuronal modules, by performing topology-based module detection. Dynamic parameters including intra-modular and inter-modular parameters are estimated in two stages, using detected hubs to connect non-overlapping neuronal modules. The contributions of PartitionMLE method are two-folds: reducing estimation errors and improving the model interpretability. Experiments about neuronal networks consisting of Hodgkin-Huxley (HH) and leaky integrate-and-firing (LIF) neurons validated the effectiveness of the PartitionMLE method, with comparison to the single-stage MLE method.

Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer's disease classification.

Brain medical imaging and deep learning are important foundations for diagnosing and predicting Alzheimer's disease. In this study, we explored the impact of different image filtering approaches and Pyramid Squeeze Attention (PSA) mechanism on the image classification of Alzheimer's disease. First, during the image preprocessing, we register MRI images and remove skulls, then apply median filtering, Gaussian blur filtering, and anisotropic diffusion filtering to obtain different experimental images. After that, we add the Squeeze and Excitation (SE) mechanism and Pyramid Squeeze Attention (PSA) mechanism to the Fully Convolutional Network (FCN) model respectively, to obtain each MRI image's corresponding feature information of disease probability map. Besides, we also construct Multi-Layer Perceptron (MLP) model's framework, combining feature information of disease probability map with age, gender, and Mini-Mental State Examination (MMSE) of each sample, to get the final classification performance of model. Among them, the accuracy of the MLP-C model combining anisotropic diffusion filtering with the Pyramid Squeeze Attention mechanism can reach 98.85%. The corresponding quantitative experimental results show that different image filtering approaches and attention mechanisms provide effective assistance for the diagnosis and classification of Alzheimer's disease.

Upregulation of OATP1A2 in human oesophageal squamous cell carcinoma cells via the HDAC6-GCN5/PCAF-H3K9Ac axis.

1. OATP1A2 overexpressed is involved in chemotherapy disposition, indicating its role in tumour development and progression.2. CHIP and siRNA were used to evaluate the status of histone acetylation at the OATP1A2 promoter. The role of OATP1A2 was analysed by gene-set enrichment and overall survival analysis.3. OATP1A2 expression levels in ESCC was notably higher than that in para-cancer tissues. OATP1A2 high expression are associated with bile salt metabolic pathway and poor prognosis. Furthermore, HDAC6 was repressed in ESCC, increasing the levels of H3K9Ac catalysed by GCN5/PCAF at the OATP1A2 promoter region.4. Abnormal histone hyperacetylation mediated by the HDAC6-GCN5/PCAF-H3K9Ac axis resulted in increased OATP1A2 expression in ESCC, and OATP1A2 may serve as a promising prognostic biomarker for ESCC.5. In conclusion, this study indicated that suppression of OATP1A2 would inhibit the progression and prognosis in ESCC.

LncRNAs link cancer stemness to therapy resistance.

Cancer stem cells (CSCs) are a cellular subpopulation accelerating cancer cell growth, invasion and metastasis and survival. After chemoradiotherapy, CSCs are enriched because of their survival advantages and lead to tumor relapse and metastasis. Elimination of CSCs is critically important for the radical treatment of human cancers. Long non-coding RNAs (lncRNAs) are a group of RNAs longer than 200 nucleotides and have no protein-coding potential. Aberrant expressions of lncRNAs are associated with human diseases including cancer. LncRNAs function as cancer biomarkers, prognostic factors and therapeutic targets. They induce cancer stemness by chromatin modification, transcriptional regulation or post-transcriptional regulation of target genes as a sponge or through assembling a scaffold complex. Several factors caused aberrant expressions of lncRNAs in CSCs such as genes mutations, epigenetic alteration and environmental stimuli. Targeting of lncRNAs has been demonstrated to significantly reverse the chemoradioresistance of CSCs. In this review, we have summarized the progress of studies regarding lncRNAs-mediated therapy resistance of CSCs and clarified the molecular mechanisms. Furthermore, we have for the first time analyzed the influences of lncRNAs on cell metabolism and emphasized the effect of tumor microenvironment on lncRNAs functions in CSCs. Overall, the thorough understanding of the association of lncRNAs and CSCs would contribute to the reversal of therapy resistance.

Identification and Functional Validation of Radioresistance-Related Genes AHNAK2 and EVPL in Esophageal Squamous Cell Carcinoma by Exome and Transcriptome Sequencing Analyses.

INTRODUCTION: Esophageal squamous cell carcinoma (ESCC) is often resistant to radiotherapy, likely due to sub-clones that survive and repopulate in the tumor. The analysis of genomic sequencing data related to radiotherapy will provide a better understanding of the intratumoral heterogeneity and genetic evolution of ESCC during radiotherapy. METHODS: We analyzed whole-exome sequencing data from pre- and post-irradiation ESCC patients at single-cell and bulk levels in public datasets. We investigated the gene functions involving radioresistance in ESCC cell lines. Furthermore, we established gene knockdown cell lines and explored the transcriptional alterations induced by RNA interference (RNAi) of these genes in KYSE-150 ESCC cell line. RESULTS: We identified three candidate genes related to radioresistance: AHNAK2, EVPL and LAMA5. Knockdown of AHNAK2 and EVPL genes led to increased radioresistance in ESCC cell lines, but not LAMA5. The transcriptome analysis indicated that these genes may regulate the expression of interleukins, interleukin receptors and chemokines by inhibiting the NF-κB and TNF signaling pathways in radioresistant ESCC cells, thereby suppressing their immune response. CONCLUSION: These data may provide new therapeutic strategies by targeting general ESCC radioresistance-related genes, which may eventually help the development of targeted therapies.

CYP2C9 inhibits the invasion and migration of esophageal squamous cell carcinoma via downregulation of HDAC.

Cytochrome P450 2C9 (CYP2C9) is involved in the metabolism of cancer drugs and exogenous carcinogens. In our study, CYP2C9 was downregulated in multiple cohorts of human esophageal squamous cell carcinoma (ESCC). Until now, its role and epigenetic regulation of CYP2C9 repression in ESCC remain poorly understood. CYP2C9 repression in collected ESCC patient tumor tissues was demonstrated by RT-qPCR and Western blot. The histone acetylation level was carried out by the treatment of histone deacetylase inhibitor TSA and RNA interference. Epigenetic analysis revealed that the increased expression of CYP2C9 in KYSE-150 and TE1 cells was characterized by inhibition of HDAC8 and HDAC1, respectively. TSA decreased the levels of HDAC occupancy around CYP2C9 promoter region greatly. Overexpression of CYP2C9 reduced the invasion and migration of ESCC cells.

Transcriptome profiling unveils GAP43 regulates ABC transporters and EIF2 signaling in colorectal cancer cells.

BACKGROUND: The growth- and plasticity-associated protein-43 (GAP43) is biasedly expressed in indigestive system and nervous system. Recent study has shown that GAP43 is responsible for the development of neuronal growth and axonal regeneration in normal nervous tissue, while serves as a specific biomarker of relapsed or refractory neuroblastoma. However, its expression pattern and function in digestive system cancer remains to be clarified. METHODS: In this study, we examined the GAP43 status with qRT-PCR and bisulfite genomic sequencing in colorectal cancer (CRC). We investigated the effect of overexpressed GAP43 in CRC cells with RNA-seq. The RNA-seq data was analyzed with DAVID and IPA. RESULTS: GAP43 was downregulated in CRC compared to the adjacent tissues. DNA methylase inhibitor 5-Aza-CdR treatment could significantly induce GAP43, indicated that the silencing of GAP43 gene in CRC is closely related to DNA methylation. Bisulfite genomic sequencing confirmed the promoter methylation of GAP43 in CRC. To explore the transcriptional alterations by overexpressed GAP43 in CRC, we performed RNA-seq and found that upregulated genes were significantly enriched in the signaling pathways of ABC transporters and ECM-receptor interaction, while downregulated genes were significantly enriched in Ribosome signaling pathway. Further Ingenuity Pathway Analysis (IPA) showed that EIF2 signaling pathway was significantly repressed by overexpression of GAP43. CONCLUSION: Our findings provide a novel mechanistic insight of GAP43 in CRC. Transcriptome profiling of overexpressed GAP43 in CRC uncovered the functional roles of GAP43 in the development of human CRC.

FAM60A promotes cisplatin resistance in lung cancer cells by activating SKP2 expression.

Cisplatin is a widely used chemotherapeutic drug in lung cancer treatment. Most cancer patients eventually develop cisplatin resistance, resulting in a poor prognosis. Previously, we identified a novel marker, family with sequence similarity 60A (FAM60A), that was responsible for resistance in cisplatin-resistant human lung adenocarcinoma A549 (A549/DDP) cells. Here, we investigated the biological effects of FAM60A in A549/DDP cells and explored the underlying molecular mechanisms to understand its functional role in cisplatin resistance. Real-time quantitative PCR and western blot analysis were used to determine the expression levels of FAM60A in A549/DDP cells. FAM60A and SKP2 were knockdown with small-interfering RNA (siRNA). Cancer cell viability was analyzed with flow cytometry. The mRNA and protein expression levels of FAM60A increased significantly and dose-dependently in A549/DDP cells following cisplatin treatment. FAM60A overexpression up-regulated MDR1 expression, inhibited caspase 3, cleaved-caspase 3, and caspase 8 expression, and prevented cancer cell death. Microarray analysis of cells transfected with siRNA against the FAM60A transcript and control samples showed that SKP2 expression was positively regulated by FAM60A. SKP2 knockdown using a short-hairpin RNA reversed the functions induced by FAM60A. These results suggest that overexpression of FAM60A in A549/DDP cells led to SKP2 upregulation and enhanced cisplatin resistance in cancer cells. These provide new insights into chemoresistance and may contribute to reversing cisplatin resistance during lung cancer treatment.

Single­cell intratumoral stemness analysis reveals the involvement of cell cycle and DNA damage repair in two different types of esophageal cancer.

Intratumoral heterogeneity, particularly the potential cancer stemness of single cancer cells, has not yet been fully elucidated in human esophageal cancer. Single­cell transcriptome sequencing of two types of esophageal adenocarcinoma (EAC) and two types of esophageal squamous cell carcinoma (ESCC) tissues was performed, and the intratumoral cancer stemness of the types of esophageal cancer were characterized at the single­cell level in the present study. By comparing the transcriptomic profiles of single cancer cells with high and low stemness in individual patients, it was revealed that the overexpression of cell cycle­associated genes in EAC cells was highly correlated with stemness, whereas overexpression of genes involved in the signaling pathways of DNA replication and DNA damage repair was significantly correlated with stemness in ESCC. High expression of these stemness­associated genes was correlated with poor prognosis of patients. Additionally, poly [ADP­ribose] polymerase(PARP)4 was identified as a novel cancer stemness­associated gene in ESCC and its association with survival was validated in a cohort of 121 patients with ESCC. These findings have profound potential implications for the use of cell cycle inhibitors in EAC and PARP inhibitors in ESCC, which may provide novel mechanistic insights into the plasticity of esophageal cancer.

Single-cell RNA sequencing reveals diverse intratumoral heterogeneities and gene signatures of two types of esophageal cancers.

Single-cell RNA sequencing and transcriptome analysis enable novel discovery and precise characterization of new cell types and states, which improves the understanding of the cellular context of tumorigenesis. Herein, we applied this powerful approach to analyze 368 single cells from three esophageal squamous cell carcinoma (ESCC) and two esophageal adenocarcinoma (EAC) tumors. Using inferred copy number variation analysis, we successfully distinguished carcinoma cells from heterogeneous cellular populations, identifying gene signatures and crucial cancer-related signaling pathways related to ESCC and EAC. In particular, we found that NOTCH signaling was exclusively activated in ESCC, but not in EAC. ESCC tumors with higher NOTCH activity were associated with significantly worse survival rates than those with lower NOTCH activity. Collectively, this study revealed that ESCC and EAC are distinct in terms of cellular transcriptome profiles, which leads to a wide range of intratumoral cellular heterogeneity. The findings suggest that different therapeutic strategies that target the differences between two types of esophageal cancers are required, guiding cancer-specific future drug development.

Single-cell Transcriptome Analyses Reveal Molecular Signals to Intrinsic and Acquired Paclitaxel Resistance in Esophageal Squamous Cancer Cells.

Paclitaxel is widely used in the combination chemotherapy for many cancers including esophageal squamous cell carcinoma (ESCC). However, the paclitaxel resistance occurs frequently in treating ESCC and the mechanism is not fully understood yet. The heterogeneity of gene expression within the drug-resistant cancer cells may be one of the major factors contributing to its resistance. In the present study, we successfully induced paclitaxel resistance in ESCC cell line KYSE-30 through low dose and long-term treatment of paclitaxel. Gene expression profiles were measured utilizing population RNA-seq and single-cell RNA-seq (scRNA-seq). 37 single cells from KYSE-30 cells and 73 single cells from paclitaxel resistant KYSE-30 cells (Taxol-R) were subjected to scRNA-seq. Weighted gene co-expression network analysis (WGCNA) of scRNA-seq data revealed two major subpopulations in both KYSE-30 and Taxol-R cancer cells. Two subpopulations based on the KRT19 expression levels in KYSE-30 cells exhibited different paclitaxel sensitivity, suggesting the existence of an intrinsic paclitaxel resistance in KYSE-30 cells. In addition, the Taxol-R cells that acquired the resistance to paclitaxel through induction were characterized with higher expressions of proteasomes but a lower expression of HIF-1 signaling genes. Furthermore, we showed that carfilzomib (CFZ), a proteasome inhibitor, could attenuate the paclitaxel resistance in Taxol-R cancer cells through activating the HIF-1 signaling. Our new finding may pave a way leading to an improvement in the treatment on cancers including ESCC by combining CFZ with paclitaxel as a novel approach for cancer therapy.